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Syndromic surveillance for local outbreak detection and awareness: evaluating outbreak signals of acute gastroenteritis in telephone triage, web-based queries and over-the-counter pharmacy sales

  • T. ANDERSSON (a1) (a2) (a3), P. BJELKMAR (a1) (a4), A. HULTH (a1), J. LINDH (a1) (a5), S. STENMARK (a6) (a7) and M. WIDERSTRÖM (a7)
  • DOI: http://dx.doi.org/10.1017/S0950268813001088
  • Published online: 15 May 2013
Abstract
SUMMARY

For the purpose of developing a national system for outbreak surveillance, local outbreak signals were compared in three sources of syndromic data – telephone triage of acute gastroenteritis, web queries about symptoms of gastrointestinal illness, and over-the-counter (OTC) pharmacy sales of antidiarrhoeal medication. The data sources were compared against nine known waterborne and foodborne outbreaks in Sweden in 2007–2011. Outbreak signals were identified for the four largest outbreaks in the telephone triage data and the two largest outbreaks in the data on OTC sales of antidiarrhoeal medication. No signals could be identified in the data on web queries. The signal magnitude for the fourth largest outbreak indicated a tenfold larger outbreak than officially reported, supporting the use of telephone triage data for situational awareness. For the two largest outbreaks, telephone triage data on adult diarrhoea provided outbreak signals at an early stage, weeks and months in advance, respectively, potentially serving the purpose of early event detection. In conclusion, telephone triage data provided the most promising source for surveillance of point-source outbreaks.

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Copyright
The online version of this article is published within an Open Access environment subject to the conditions of the Creative Commons Attribution-NonCommercial-ShareAlike licence <http://creativecommons.org/licenses/by-nc-sa/3.0/>. The written permission of Cambridge University Press must be obtained for commercial re-use.
Corresponding author
*Author for correspondence: Dr T. Andersson, Swedish Institute for Communicable Disease Control (SMI), 171 82 Solna, Sweden. (Email: tom.andersson@msb.se)
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2. RDFrickerJr. Some methodological issues in biosurveillance. Statistics in Medicine 2011; 30: 403415.

3.DL Buckeridge . Outbreak detection through automated surveillance: a review of the determinants of detection. Journal of Biomedical Informatics 2007; 40: 370379.

4.M Berger , R Shiau , JM Weintraub . Review of syndromic surveillance: implications for waterborne disease detection. Journal of Epidemiology and Community Health 2006; 60: 543550.

5.SS Morse . Public health surveillance and infectious disease detection. Biosecurity and Bioterrorism : Biodefense Strategy, Practice, and Science 2012; 10: 616.

6.DL Cooper , Can syndromic surveillance data detect local outbreaks of communicable disease? A model using a historical cryptosporidiosis outbreak. Epidemiology and Infection 2006; 134: 1320.

9. MLKirian , JMWeintraub . Prediction of gastrointestinal disease with over-the-counter diarrheal remedy sales records in the San Francisco Bay Area. BMC Medical Informatics and Decision Making 2010; 10: 39.

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11.A Hulth , G Rydevik , A Linde . Web queries as a source for syndromic surveillance. PLoS One 2009; 4: e4378.

13.S Unkel , Statistical methods for the prospective detection of infectious disease outbreaks: a review. Journal of the Royal Statistical Society: Series A (Statistics in Society) 2012; 175: 4982.

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  • ISSN: 0950-2688
  • EISSN: 1469-4409
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Supplementary Materials

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